de.aitools.dm.clustering.algorithms.hac
Class Median

java.lang.Object
  de.aitools.dm.clustering.algorithms.hac.Median

All Implemented Interfaces:

HACClusterMethod

public final class Median
extends java.lang.Object
implements HACClusterMethod

Much like the Centroid-Method, but the centroid is computed as if the two clusters would have had the same number of data points. Note that this method is not monotone.
This method needs a distance measure as Proximity.

Version:

$Id: Median.java,v 1.1 2011/06/22 14:22:51 dogu3912 Exp $

Author:

johannes.kiesel(/\t)uni-weimar.de

Constructor Summary

Median()

Method Summary

double

simRQ(double simAB, double simAQ, double simBQ, int sizeA, int sizeB, int sizeQ) Equation (from Tan et al.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Median

public Median()

Method Detail

simRQ

public double simRQ(double simAB,
                    double simAQ,
                    double simBQ,
                    int sizeA,
                    int sizeB,
                    int sizeQ)

Description copied from interface: HACClusterMethod

Equation (from Tan et al. (2006) p. 524, see HAC for full reference):
sim(R,Q) = α_a * sim(A,Q) + α_b * sim(B,Q) + β * sim(A,B) + γ * |sim(A,Q) - sim(B,Q)|
Where α_a, α_b, β and γ depend on the method to use.
See the class description of the concrete implementation for information about these parameters.
Cluster A and cluster B are merged to form cluster R. This method calculates the proximity of R to a cluster Q.

Specified by:

simRQ in interface HACClusterMethod

Parameters:

simAB - Proximity between A and B

simAQ - Proximity between A and Q

simBQ - Proximity between B and Q

Returns:

simRQ, the proximity between R and Q